Arthroscopic management of isolated partial‐thickness rotator cuff tears
Bibliographic record
Abstract
PURPOSE: The aim of the present study is to provide a comprehensive review on the surgical outcomes following arthroscopic treatments of partial-thickness rotator cuff tears (PT-RCTs) and to compare the postoperative American Shoulder and Elbow Surgeons (ASES) score following in situ transtendon repair and tear completion, followed by repair. METHODS: Medline, EMBASE, Scopus, CINAHL and CENTRAL bibliographic databases were searched. Papers including patients with PT-RCTs of any grade who underwent treatment using debridement, in situ transtendon repair, tear completion and repair or bioinductive collagen implants were reviewed. Primary PT-RCTs were the sole indication for surgery. Primary postoperative outcomes assessed included the ASES score, the Absolute Constant-Murley score, the Simple Shoulder Test, the Visual Analogue Scale, the University of California-Los Angeles Shoulder Scale, the Western Ontario Rotator Cuff Score, range of motion, complications and revisions. A meta-analysis of comparative studies compared the postoperative ASES score between patients treated with in situ transtendon repair versus tear completion repair. RESULTS: = 86%), and effect sizes ranged from -0.49 in favour of the tear completion and repair technique to an effect size of +1.07 favouring in situ transtendon repair. The overall effect size of 0.02 suggests an equivalence between the two techniques in terms of the ASES score. Two studies with a total sample size of 111 patients reported on debridement, and four studies with a total sample size of 155 patients reported on bioinductive collagen implants. CONCLUSION: Debridement alone is suitable for Ellman grades I-II PT-RCTs. In situ transtendon and tear completion repair techniques yield similar postoperative outcomes. Bioinductive collagen implants hold promise but lack long-term efficacy data. High-quality comparative studies are needed to determine the best treatment for PT-RCTs. LEVEL OF EVIDENCE: Level IV.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.002 | 0.008 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.003 | 0.002 |
| Bibliometrics | 0.003 | 0.002 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 0.000 |
| Insufficient payload (model declined to judge) | 0.003 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".